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Author: search.filters.author.Bertsche, BerndSubject: search.filters.subject.600

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    Systematic method for axiomatic robustness-testing (SMART)
    (2014) Kemmler, Stefan; Bertsche, Bernd
    SMART (Systematic Method for Axiomatic Robustness-Testing) is a method for the development of robust and reliable products. It combines elements from the robust design methodology with a holistic approach by using Axiomatic Design (AD) and the Taguchi Method (TM). These two methods were established and expanded by N.P. Suh [1990] (AD) and G. Taguchi [1949] (TM). SMART is based on the chronological sequence of the four phases of the Product Development Process (planning, conception, design and development) according to the VDI Guideline 2221. Using this chronological basis, the three process steps (System, Parameter and Tolerance Design) of the Taguchi Method are classified and integrated accordingly. The AD method is applied to the systematic examination of the robustness of designs. During the conceptual stage, one or more designs are generated by means of AD. AD also helps analyze the design’s complexity from the perspective of possible design modifications, thus assuring robust solutions. If a design has already been generated but needs improvement as things developed, AD is used as well. The design may not necessarily be changed in its basic structure but is examined in terms of its complexity. The results of AD support the setup of the P-Diagram according to Taguchi either after the conceptual stage or the design stage of the product. The following step is the Design of Experiments (DoE) of the product’s design parameters and noise factors that occur during its utilization. Testing may either be carried out by virtual or real tests. After analyzing the results of the tests, the design should be optimized accordingly in order to increase the robustness. A predicted reliability determination is possible as well. The last step is the adjustment of the tolerances of the design for cost optimization purposes. After a final robust design has been established, the actual durability and reliability of the design can be determined on the basis of reliability testing using Design for Reliability (DFR) methods. Basically, SMART can be used both in the initial stages as well as in the more developed stages of the development process.
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    Method for the development of a functional adaptive simulation model for designing robust products
    (2014) Kemmler, Stefan; Dazer, Martin; Leopold, Tobias; Bertsche, Bernd
    Products have to ensure their function under the inuence of internal and external noise factors in order to remain competitive in the current market. Therefore the step of designing robust products should be integrated in early stages of the Product Development Process (PDP). Robust products are developed using the Robust Design Method SMART (Systematic Method for Axiomatic Robustness-Testing). Thus far, SMART was applied and veri ed based on a simple mechanical machine element. In this paper, the method will be applied to a complex technical system. Additionally, the confict of aiming between the high e orts and the level of detail in the creation of a simulation model are discussed. This confict is brought about owing to the complex functionality of the design. In order to solve the conict, an approach is given for the creation of an adjusted simulation model. Short simulation times are an advantage for the analysis of parameters regarding robustness. The adaptive simulation model discussed in this paper is based on a exible and equation-based model, which is extended with local -structural-mechanical SUB-models for a more detailed analysis. This approach o ers the option of obtaining rst insights about the functionality of the product and the opportunity to complement the simulation model iteratively for the following design phases. This approach complements SMART on the one hand in the simulative design of robust design parameters and, on the other hand, in their reliability prediction in both the Parameter Design and Tolerance Design phase.